This study examines the anthropogenic determinants of land take using a spatially extended STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) framework applied to panel data from 1,600 municipalities in Bavaria, Germany, covering the period from 2014–2022. A Spatial Durbin Error Model is employed to account for spatial dependence and spillover effects across neighboring municipalities. Moreover, literature defines affluence typically as income or GDP per capita indicating the level of affluence of private households or regions. In contrast, the results of this paper demonstrate that (also) public affluence is a suitable indicator for explaining land take. The results show that population and public affluence exert positive local effects on land take, while urban density significantly restrains land take. Moreover, a non-linear Environmental Kuznets Curve relationship for public affluence is observed, which materializes also through spatial spillover effects. Building permissions emerge as a key policy-related driver, generating positive indirect effects that propagate land consumption across adjacent municipalities. These findings highlight that land take is not only shaped by local conditions but evolves as a spatially interconnected process driven by fiscal capacity and planning decisions. The study underscores the need for coordinated, multi-regional land-use policies and highlights the analytical value of small-scale spatial STIRPAT applications in capturing environmentally relevant development dynamics.